By Pete Stiglich
Explains why integrating healthcare datasets is hard when metadata is incomplete—especially as data exchange accelerates. The post proposes creating a standard ‘what we need to know about data’ checklist that goes beyond basic field name/length. It includes business names, definitions (avoiding tautologies), keys and uniqueness, valid values/domains, formats, conditions/exclusions, relationships/cardinality, and security/privacy indicators (e.g., PHI). By assessing metadata completeness up front, teams can estimate integration effort, price external data onboarding, design ETL and quality checks with less rework, and build stronger data contracts than an XSD alone.
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Pete Stiglich: Trusted Expert in Data Architecture & Modeling
Pete has over 30 years of data architecture, data management, and analytics experience, most of that time as a consultant in industries such as government, finance, healthcare, insurance, and more. He is an industry thought leader in data architecture and data modeling and has developed and taught many courses on these topics. Pete enjoys helping clients solve complex data problems, leveraging proven approaches such as “Modeling the business before modeling the solution” which provides a benefit to clients that many IT professionals miss.
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